Community detection techniques seek to find densely connected clusters within large networks. However, it raises privacy concerns, like the personal reveal or community member’s group information, and contradicts the desire of individual or group to remain anonymous. As a result, concealing a specific community in a network to avoid the finding by methods of community detection becomes critical. Some previous work focuses on hiding some sensitive communities in order to conceal the community association of the focused vertices. Community deception is achieved by changing the links between the vertices in a network minimally so that a specific community can hide as much as possible from a community detection algorithm. This article discusses a study on previously proposed community deception techniques, as well as a discussion of the performance measures used to evaluate community deception methods.